Supply chain, enterprise and site planning applications and environments are widely used by manufacturing entities for decision support and to help manage operations. Decision support environments for supply chain, enterprise, and site planning have evolved from single-domain, monolithic environments to multi-domain, monolithic environments. Conventional planning software applications are available in a wide range of products offered by various companies. These decision support tools allow entities to more efficiently manage complex manufacturing operations. However, supply chains are generally characterized by multiple, distributed and heterogenous planning environments. Thus, there are limits to the effectiveness of conventional environments when applied to the problem of supply chain planning due to monolithic application architectures. Further, these problems are exacerbated when there is no one "owner" of the entire supply chain.
It is desirable for the next evolutionary step for planning environments to establish a multi-domain, heterogenous architecture that supports products spanning multiple domains, as well as spanning multiple engines and products. The integration of the various planning environments into a seamless solution can enable inter-domain and inter-enterprise supply chain planning. Further, an important function provided by some planning applications is the optimization of the subject environment rather than simply tracking transactions. In particular, the RHYTHM family of products available from I 2 TECHNOLOGIES provide optimization functionality. However, with respect to planning at the enterprise or supply chain level, many conventional applications, such as those available from SAP, use enterprise resource planning (ERP) engines and do not provide optimization.
The success or failure of an enterprise can depend to a large extent on the quality of decision making within the enterprise. Thus, decision support software, such as I 2 TECHNOLOGIES' RHYTHM family of products, that support optimal decision making within enterprises can be particularly important to the success of the enterprise. In general, optimal decisions are relative to the domain of the decision support where the domain is the extent of the "world" considered in arriving at the decision. For example, the decision being made may be how much of a given item a factory should produce during a given time period. The "optimal" answer depends on the domain of the decision. The domain may be, for example, just the factory itself, the supply chain that contains the factory, the entire enterprise, or the multi-enterprise supply chain. (The latter two can be considered to be larger domains or multiple domains.) Typically, the larger the domain of the decision support, the more optimal the decision will be. Consequently, it is desirable for decision support software to cover ever larger domains in the decision making process. Yet, this broadening of coverage can create significant problems.